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Orthopaedic Proceedings
Vol. 102-B, Issue SUPP_10 | Pages 4 - 4
1 Oct 2020
Brekke AC Wu CJ Hinton ZW Kim BI Ryan SP Bolognesi MP Seyler TM
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Introduction

Survival after contemporary solid organ transplant (SOT) is increasing, and demand for total hip arthroplasty (THA) among SOT recipients is rising accordingly. The purpose of this study is to compare the perioperative outcomes and short-term implant- and patient-survivorship of contemporary THA following the most common types of SOT.

Methods

Among SOT recipients, 119 primary THAs (92 patients, 39% female) were performed at a single institution from 2000–2020 and were retrospectively reviewed at a mean follow-up of 3.6yrs. Revisions, conversion to THA and multiple organs transplanted were excluded. The most common SOT was renal (39%), followed by lung (34%), liver (18%) and heart (8%). Demographics, peri-operative outcomes, 90-day re-admissions, re-operations and mortality were compared between SOT groups using chi-squared, Fisher's exact, Wilcoxon tests and Cox proportional hazard ratios.


Orthopaedic Proceedings
Vol. 101-B, Issue SUPP_12 | Pages 15 - 15
1 Oct 2019
Plate JF Ryan SP Black C Howell CB Jiranek WA Bolognesi MP Seyler TM
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Introduction

Alternative payment models for total hip arthroplasty (THA) were initiated by the Center for Medicare and Medicaid Services (CMS) to decrease overall healthcare cost by optimizing healthcare delivery. The associated shift of financial risk to participating institutions has been criticized to introduce patient selection in order to avoid potentially high cost of care. This study aimed to evaluate the impact of the Comprehensive Care for Joint Replacement (CJR) model on patient selection, care delivery and hospital costs at a single care center.

Methods

This is a retrospective review of THA patient from July 2015-December 2017 was performed. Patient were stratified by insurance type (Medicare and commercial insurance) and whether care was provided before or after implementation of the CJR bundle. Patient age, gender, and BMI, as well as Elixhauser comorbidities and ASA scores were analyzed. Delivery of care variables including surgery duration, discharge disposition, length of stay, and direct hospital costs were compared before and after CJR implementation.


Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_13 | Pages 23 - 23
1 Oct 2018
Goltz D Ryan S Howell C Jiranek WA Attarian DE Bolognesi MP Seyler TM
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Introduction

The Comprehensive Care for Joint Replacement (CJR) model for total hip arthroplasty (THA) involves a target reimbursement set by the Center for Medicare and Medicaid Services (CMS). Many patients exceed these targets, but predicting risk for incurring these excess costs remains challenging, and we hypothesized that select patient characteristics would adequately predict CJR cost overruns.

Methods

Demographic factors and comorbidities were retrospectively reviewed in 863 primary unilateral CJR THAs performed between 2013 and 2017 at a single institution. A predictive model was built from 31 validated comorbidities and a base set of 5 patient factors (age, gender, BMI, ASA, marital status). A multivariable logistic regression model was refined to include only parameters predictive of exceeding the target reimbursement level. These were then assigned weights relative to the weakest parameter in the model.


Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_13 | Pages 54 - 54
1 Oct 2018
Bolognesi MP Ryan S Goltz D Howell CB Attarian DE Jiranek WA Seyler TM
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Introduction

Hip fractures are a common pathology treated by Orthopaedic surgeons. The Comprehensive Care for Joint Replacement (CJR) model utilizes risk stratification to set target prices for these patients undergoing hemiarthroplasty or total hip arthroplasty (THA). We hypothesized that sub-specialty arthroplasty surgeons would be able to treat patients at a lower cost compared to surgeons of other specialties during cases performed while on call.

Methods

Patients with hemiarthroplasty or THA for hip fractures were retrospectively collected from June, 2013, to May, 2017, from a single tertiary referral center. Demographic information and outcomes based on length of stay (LOS), net payment, and target payment were collected. Patients were then stratified by surgeon subspecialty (arthroplasty trained vs. other specialty). Univariable and multivariable analysis for payment based on treating surgeon was then performed.